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Two-stage Gradient-based Iterative Estimation Methods for Controlled Autoregressive Systems Using the Measurement Data

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Abstract

This paper considers the parameter identification problems of controlled autoregressive systems using observation information. According to the hierarchical identification principle, we decompose the controlled autoregressive system into two subsystems by introducing two fictitious output variables. Then a two-stage gradient-based iterative algorithm is proposed by means of the iterative technique. In order to improve the performance of the tracking the time-varying parameters, we derive a two-stage multi-innovation gradient-based iterative algorithm based on the multi-innovation identification theory. Finally, an example is provided to illustrate the effectiveness of the proposed algorithms.

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Authors and Affiliations

  1. Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, the School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, 430068, P. R. China

    Feng Ding, Lei Lv, Jian Pan & Xiangkui Wan

  2. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao, 266061, P. R. China

    Feng Ding

  3. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, P. R. China

    Xue-Bo Jin

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  1. Feng Ding
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Correspondence to Feng Ding.

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Recommended by Associate Editor Yongping Pan under the direction of Editor Young IL Lee. This work was supported by the National Natural Science Foundation of China (no. 61571182).

Feng Ding received his B.Sc. degree from the Hubei University of Technology (Wuhan, China) in 1984, and his M.Sc. and Ph.D. degrees both from the Tsinghua University, in 1991 and 1994, respectively. He has been a professor in the School of Internet of Things Engineering at the Jiangnan University (Wuxi, China) since 2004. His current research interests include model identification and adaptive control. He authored four books on System Identification.

Lei Lv was born in Jiaocheng, Shanxi Province, China. He received his B.Sc. degree from the Jiangsu Ocean University (Lianyungang, China) in 2017. He is now a master student at the Hubei University of Technology, Wuhan, China. His research interests include system identification and control theory.

Jian Pan was born in Wuhan, China. He received his B.Sc. degree from the Hubei University of Technology (Wuhan, China) in 1984. From 1984 to 2002, he was with Department of Electrical Engineering and Computer Science, Hubei University of Technology. He has been a Professor in School of Electrical and Electronic Engineering, Hubei University of Technology. His currently research interests include control science and engineering, computer control systems, power electronics. He respectively received Hubei Province Science and Technology Progress Awards, won second prize in 2003 and 2017, third prize in 2005 and 2012. He also received Wuhan City Science and Technology Progress Awards, won third prize in 2012 and second prize in 2014. He is currently a director of Hubei Association of Automation and a director of Wuhan Power Supply Society.

Xiangkui Wan received his M.S. and Ph.D. degrees in the Mechatronic Engineering from Chongqing University, in 2002 and 2005, respectively. He is currently a professor in the School of Elec-trical and Electronic Engineering, Hubei University of Technology, Wuhan, China. His research interests include digital signal processing, biomedical signal processing and analysis, biomedical modeling and simulation, cardiovascular system.

Xue-Bo Jin received her B.E. degree in industrial electrical and automation and a Master degree in industrial automation from Jilin University, Jilin, China, in 1994 and 1997, and her Ph.D. degree in control theory and control engineering from Zhejiang University, Zhejiang, China, in 2004. From 1997 to 2012 she was with College of Informatics and Electronics, Zhejiang Sci-Tech University. Since 2012 she has been with College of Computer and Information Engineering, Beijing Technology and Business University as a Professor. Her research interests include multisensor fusion, statistical signal processing, video/image processing, robust filtering, Bayesian theory and Time series analysis.

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Ding, F., Lv, L., Pan, J. et al. Two-stage Gradient-based Iterative Estimation Methods for Controlled Autoregressive Systems Using the Measurement Data. Int. J. Control Autom. Syst. 18, 886–896 (2020). https://doi.org/10.1007/s12555-019-0140-3

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